Abstract T P119: Challenges Associated with Access to Stroke Rehabilitation for Patients with Cognitive Impairment in Toronto
Bibliographic record
Abstract
Background: Cognitive Impairment (CI) affects up to 60% of stroke survivors and is associated with poorer recovery and decreased function. Toronto clinicians report limited access to inpatient rehabilitation for stroke patients with CI. Purpose: To inform system planning that aligns with best practice for stroke patients with CI, the Toronto Stroke Networks examined: 1) access to inpatient rehabilitation services for stroke patients with CI; 2) facility differences with respect to referral decisions; and 3) the frequency of documented standardized cognitive screening (SCS) in inpatient rehabilitation referrals. Methods: Data were abstracted from the E-Stroke Rehab Referral System for fiscal years 2012-2014. Initial high intensity rehabilitation (HIR) referrals for 5 rehabilitation facilities in Toronto were analyzed to examine: percentage of referrals accepted, declined, and declined due to CI, and percentage of referrals reporting SCS in referral documentation. These data were further stratified by facility. A survey of cognitive rehabilitation was completed across 6 rehabilitation facilities. Results: There are no cognitive rehabilitation services that cater specifically to stroke patients reported in Toronto. Of the total number of HIR referrals (n=5005), 68.3% of initial referrals were accepted and 18.2% declined. Of the declined referrals (n=910), 17.5% were declined due to CI with variability across the 5 rehabilitation facilities ranging from 0.6 to 46.5%. Further, when examining referrals that were pending a decision or declined due to CI (n=508), 78.5% (range 48-100%) of these referrals across, 10 referring acute care facilities, had no documented SCS. Conclusions: Stroke patients with CI do not have adequate or consistent access to stroke rehabilitation across sites within Toronto. Additionally, there is a lack of documented SCS in rehabilitation referrals, which could impact access to rehabilitation. This work will further inform educational initiatives that support increased access to inpatient rehabilitation for persons with stroke and CI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".